Bike and run pacing on downhill segments predict Ironman triathlon relative success

Performance and pacing of professional IRONMAN triathletes: the fastest IRONMAN World Championship ever-IRONMAN Hawaii 2022

Pacing during cycling and running in an IRONMAN triathlon has been investigated in only one study with elite IRONMAN triathletes. We have, however, no knowledge of how professional triathletes pace during an IRONMAN World Championship. To investigate the split-by-split speed, pacing strategies and pacing variability in professional female and male IRONMAN World Championship participants in the fastest IRONMAN World Championship ever in IRONMAN Hawaii 2022. For both cycling and running, 25 specific split times were recorded in each discipline. The best 30 men and 30 women overall were chosen from the official IRONMAN website database for further analysis. They were divided into three performance groups: Top 10, 11-20th place, and 21st-30th place. Mean speed, individual linear regressions with the corresponding correlation coefficients, and coefficient of variation were calculated to assess split-by-split speed, pacing strategies, and pacing variability, respectively. In both men's and women's cycling and running segments, the top ten participants exhibited faster split times compared to the slower performance groups. Notably, no discernible differences existed between the 11-20th and 21st-30th place in men's cycling and women's running times. Conversely, in men's running and women's cycling segments, those in the 11-20th place displayed quicker times than those in the 21st-30th place. In the cycling segment across all groups, men demonstrated a more negative pacing pattern (indicating an increase in speed), whereas women exhibited more consistent pacing. In the running segment, the top 10 men and all women's groups showcased relatively similar slightly positive pacing profiles. However, men ranking 11-20th and 21st-30th displayed more pronounced positive pacing strategies, implying a more significant decline in speed over time. In terms of cycling, the variability in pacing remained relatively consistent across the three performance groups. Conversely, during the running segment, the top ten male triathletes and those in the 11-20th place displayed lower pacing variability than their counterparts in the 21st-30th position place and all women's groups. In summary, performance and pacing were examined in professional male and female IRONMAN World Championship participants during IRONMAN Hawaii 2022. Top performers showed faster cycling and running split times, with differences in pacing strategies between sexes. The pacing was more consistent in cycling, while running pacing varied more, particularly among male triathletes in different performance groups.

Uneven but Conservative Pacing Is Associated With Performance During Uphill and Downhill Running

PURPOSE

To investigate the relationship between pacing strategy and performance during uphill and downhill running-specifically, what distribution of energy corresponds to faster race finish times between and among participants.

METHODS

Eighteen years of race data from a 10.2-mile running race with an uphill first half and a downhill second half were analyzed to identify relationships between pacing and performance. A pacing coefficient (PC), equal to a participant's ascent time divided by finishing time (FT), was used to define each participant's pacing strategy. The American College of Sports Medicine metabolic running equation was used to estimate energy expenditure during the ascent, descent, and total race. Statistical analyses compared participants' PC to their FT and finishing place within their age and gender category. Additionally, FT and finishing place were compared between groups of participants who exhibited similar pacing strategies.

RESULTS

PCs were positively associated with faster FTs (r2 = .120, P < .001) and better finishing positions (r2 = .104, P < .001). PCs above .600 were associated with the fastest average FTs and best average finishing position within age and gender categories (all P ≤ .047).

CONCLUSIONS

Participants performed the best when energy expenditure increased no more than 10.4% during the uphill portion compared to their overall average. It is not possible to state that overly aggressive uphill efforts resulted in premature fatigue and thus slower decent times and worse race performance. However, participants should still avoid overly aggressive uphill pacing, as performance was associated with larger PCs.

Pacing strategy of a wheelchair athlete in a 5x and 10x Ironman ultra triathlon: a case study

OBJECTIVE

For disabled athletes such as wheelchair athletes, there is no knowledge about competing and pacing during a long-distance triathlon such as an Ironman triathlon. This study aimed to investigate the pacing strategy of a paraplegic wheelchair athlete competing and finishing a Quintuple Iron ultra-triathlon (i.e., five times 3.8 km swimming, 180 km handbike cycling and 42.195 km wheelchair racing in five days) and a Deca Iron ultra-triathlon (10 times the same distance in 10 days).

METHODS

Data from an ultra-distance triathlon race (Swissultra) covering 5x and 10x Ironman distance were collected. Official performance data were acquired from the race organizer's website and athlete's personal information from the athlete through online interviews. The athlete is a man born in 1962, the races analysed in this study were held in the summer of 2017 (5x) and 2019 (10x). The split times for swimming, cycling and running, the overall race times for each Ironman and the lap times in cycling (handbike) and running (wheelchair) were analysed.

RESULTS

The athlete finished the Quintuple Iron ultra-triathlon in an overall race time of 66:28:31 h:min:s and the Deca Iron ultra-triathlon in 137:03:20 h:min:s. He adopted an even pacing in both races in split disciplines and for overall race time.

CONCLUSION

The paraplegic wheelchair athlete was able to finish both a Quintuple and a Deca Iron ultra-triathlon by adopting an even pacing in all split disciplines and for overall race time.IMPLICATIONS FOR REHABILITATIONTriathlon is a growing sport among athletes with spinal cord injury.Ultra-triathlons are ultra-endurance events and pacing is a key aspect to a successful race regardless the athlete's category.An athlete with a spinal cord injury finished a 5x and 10x Ironman ultra-triathlon applying an even pacing strategy.

The effects of a 226-km ironman triathlon race on bone turnover in amateur male triathletes

BACKGROUND

The purpose of this study was to investigate the effects of an Ironman-distance triathlon on bone metabolism.

METHODS

Nine recreational male triathletes (39.7±8.2 years old) were voluntarily recruited before a 226-km Ironman triathlon race. Baseline blood samples were collected >1 hour before race. Serial post-race blood sampling time points included immediately (0hr), 1 hour (1hr), 1 day (d), 3 d, and 5 d after the Ironman race.

RESULTS

Serum muscle damage markers, serum myoglobin, creatine kinase (CK) and lactate dehydrogenase (LDH) revealed significant post-race peak values immediately, 1hr and 1d after the race, respectively. Except for the marginally higher serum CK and myoglobin at 5d (P=0.01~0.05), all post-race serum levels of muscle damage markers were significantly higher than baseline levels (P<0.01). Serum phosphorus values were significantly higher immediately (0hr) after the Ironman race. Serum osteocalcin, an index specific to bone formation, showed a significant decrease at time points 0hr and 1hr, but a significant increase 1 day after (P<0.01) and a marginal increase 3 and 5 days after (P=0.01~0.05) the race. No difference was shown in type I collagen C-telopeptide (CTX-1), a bone resorption marker. Pearson's correlation between serum osteocalcin and CTX-1 was done at each time point, and significant correlation was shown on the 5th d after the race (r=0.591, P<0.05).

CONCLUSIONS

An Ironman-distance contest induces a bone-formative-favoring turnover during the post-race period for amateur male triathletes.

The Effect of Aging on Pacing Strategies in Short and Long Distance Duathlon

Background/Study context: Many studies have been conducted on the triathlon during the last several years; however, less information exists with regards to duathlon (i.e., Run 1, Bike and Run 2). The aim of the present study was to examine the effect of age on pacing (i.e., the relative contribution - % - of each discipline and transition times - Transition 1 and Transition 2 - to overall race time) of duathletes competing either to short (i.e., 10 km Run 1, 50 km Bike and 5 km Run 2) or long distance (i.e., 10 km Run 1, 150 km Bike and 30 km Run 2).

METHODS

We analyzed 6,671 finishes (women's, n= 1,037, age 36.6 ± 9.1 years; men's, n= 5,634, 40.0 ± 10.0 years) of 3,881 duathletes competing in 'Powerman Zofingen', the World Championship, from 2003 to 2017, in both the short and the long distance race.

RESULTS

A large discipline×distance interaction on relative time (%) was observed in the short distance (p < .001, η²_p = .936); 24.7%, 57.4%, and 15.8% were spent in Run 1, Bike, and Run 2, respectively. In the long distance, the relative contribution of disciplines was 8.0%, 59.0%, and 32.1%, respectively. A trivial discipline×sex interaction on relative time (%) was shown in the short (p < .001, η²_p = .007) and long distance (p < .001, η²_p = .016). In the short distance, a small discipline×age group interaction on relative time (%) was found (p < .001, η²_p = .030) with younger age groups spending less time (%) in Run 1, Transition 1 and Transition 2, and older groups less time (%) in Bike and Run 2. In the long distance, a moderate discipline×age group interaction on relative time (%) was observed (p < .001, η²_p = .077) with younger age groups spending less time (%) in Run 1, Transition 1, Transition 2 and Run 2, and older groups less time (%) in Bike.

CONCLUSIONS

These findings suggest that younger duathletes are relatively faster in Run 1 and transitions, and older duathletes in Bike in both distances. However, older duathletes are relatively faster in Run 2 in the short distance and younger duathletes are relatively faster in Run 2 in the long distance. The magnitude of the combined effect of discipline and age group on pacing was larger in the long than in the short distance. Therefore, athletes and coaches should be aware of the variation of pacing by age group and distance of a duathlon race such as 'Powerman Zofingen'.

The Combined Effect of Aging and Performance Level on Pacing in Duathlon - the "ITU Powerman Long Distance Duathlon World Championships"

The role of age and performance level has been investigated in runners such as marathoners, but not in multi-sports athletes such as duathletes (running, cycling, and running). Thus, the aim of the present study was to examine the combined effects of aging and performance level on pacing of duathletes competing in two different race distances. Pacing (defined as the relative contribution of cycling time, %, to the overall race time) was analyzed for 6,671 duathletes competing from 2003 to 2017 in the short distance race (10 km first run, 50 km cycling and 5 km second run) or long distance race (10 km first run, 150 km cycling and 30 km second run) of “Powerman Zofingen,” the “ITU Powerman Long Distance Duathlon World Championships.” Men were faster, older, and spent less time (%) in cycling than women in both distances races (p < 0.001). Younger age groups spent more time (%) in cycling than their older counterparts in women (both short and long distance, p = 0.036, η_p² = 0.031, p = 0.025, η_p² = 0.044, respectively) and men (long distance race, p < 0.001, η_p² = 0.016). Fast performance groups spent more time (%) in cycling than their slower counterparts in short (women, p < 0.001, η_p² = 0.057; men, p < 0.001, η_p² = 0.035) and long distance (women, p < 0.001, η_p² = 0.070; men, p < 0.001, η_p² = 0.052). A small age group × performance group interaction on cycling time (%) was observed in the men’s short distance (p = 0.001, η_p² = 0.020) – but not in the long distance or in women – with smaller differences between performance groups in the older than in the younger age groups. Women, young and fast duathletes were relatively slower in cycling than men, old and slow duathletes; that was, old duathletes were relatively faster in cycling than in running. Moreover, there was indication that the difference in pacing among performance groups might be attenuated with aging. Since fast duathletes were relatively faster in running than in cycling, slow duathletes should be encouraged to cycle slower and run faster.

Tracking Performance in Endurance Racing Sports: Evaluation of the Accuracy Offered by Three Commercial GNSS Receivers Aimed at the Sports Market

Advances in global navigation satellite system (GNSS) technology have resulted in smaller and more accurate GNSS receivers, which have become increasingly suitable for calculating instantaneous performance parameters during sports competitions, for example by providing the difference in time between athletes at any location along a course. This study investigated the accuracy of three commercially available GNSS receivers directed at the sports market and evaluated their applicability for time analysis in endurance racing sports. The receivers evaluated were a 1 Hz wrist-worn standalone receiver (Garmin Forerunner 920XT, Gar-920XT), a 10 Hz standalone receiver (Catapult Optimeye S5, Cat-S5), and a 10 Hz differential receiver (ZXY-Go). They were validated against a geodetic, multi-frequency receiver providing differential position solutions (accuracy < 5 cm). Six volunteers skied four laps on a 3.05 km track prepared for cross-country skiing, with all four GNSS receivers measuring simultaneously. Deviations in position (horizontal plane, vertical, direction of travel) and speed (horizontal plane and direction of travel) were calculated. In addition, the positions of all receivers were mapped onto a mapping trajectory along the ski track, and a time analysis of all 276 possible pairs of laps was performed. Specifically, the time difference between any two skiers for each integer meter along the track was calculated. ZXY-Go, CAT-S5, and GAR-920XT had horizontal plane position errors of 2.09, 1.04, and 5.29 m (third quartile, Q3), and vertical precision 2.71, 3.89, and 13.35 m (interquartile range, IQR), respectively. The precision in the horizontal plane speed was 0.038, 0.072, and 0.66 m s^-1 (IQR) and the time analysis precision was 0.30, 0.13, and 0.68 s (IQR) for ZXY-Go, Cat-S5, and Gar-920XT, respectively. However, the error was inversely related to skiing speed, implying that for the low speeds typically attained during uphill skiing, substantially larger errors can occur. Specifically, at 2.0 m s^-1 the Q3 was 0.96, 0.36, and 1.90 s for ZXY-Go, Cat-S5, and Gar-920XT, respectively. In summary, the differential (ZXY-Go) and 10 Hz standalone (Cat-S5) receivers performed substantially better than the wrist-worn receiver (Gar-920XT) in terms of horizontal position and horizontal speed calculations. However, all receivers produced sub-second accuracy in the time analysis, except at very low skiing speeds.

Pacing Strategy of a Full Ironman Overall Female Winner on a Course With Major Elevation Changes

Pryor, JL, Adams, WM, Huggins, RA, Belval, LN, Pryor, RR, and Casa, DJ. Pacing strategy of a full Ironman overall female winner on a course with major elevation changes. J Strength Cond Res 32(11): 3080-3087, 2018-The purpose of this study was to use a mixed-methods design to describe the pacing strategy of the overall female winner of a 226.3-km Ironman triathlon. During the race, the triathlete wore a global positioning system and heart rate (HR)-enabled watch and rode a bike outfitted with a power and cadence meter. High-frequency (every km) analyses of mean values, mean absolute percent error (MAPE), and normalized graded running pace and power (accounting for changes in elevation) were calculated. During the bike, velocity, power, cadence, and HR averaged 35.6 km·h, 199 W, 84 rpm, and 155 b·min, respectively, with minimal variation except for velocity (measurement unit variation [MAPE]: 7.4 km·h [20.3%], 11.8 W [7.0%], 3.6 rpm [4.6%], 3 b·min [2.3%], respectively). During the run, velocity and HR averaged 13.8 km·h and 154 b·min, respectively, with velocity varying four-fold more than HR (MAPE: 4.8% vs. 1.2%). Accounting for elevation changes, power and running pace were less variable (raw [MAPE] vs. normalized [MAPE]: 199 [7.0%] vs. 204 W [2.7%]; 4:29 [4.8%] vs. 4:24 min·km [3.6%], respectively). Consistent with her planned pre-race pacing strategy, the triathlete minimized fluctuations in HR and watts during the bike and run, whereas velocity varied with changes in elevation. This case report provides observational evidence supporting the utility of a pacing strategy that allows for an oscillating velocity that sustains a consistent physiological effort in full Ironman races.

Deviation from goal pace, body temperature and body mass loss as predictors of road race performance

OBJECTIVES

The purpose of this study was to examine the relationship between pacing, gastrointestinal temperature (T_GI), and percent body mass loss (%BML) on relative race performance during a warm weather 11.3km road race.

DESIGN

Observational study of a sample of active runners competing in the 2014 Falmouth Road Race.

METHODS

Participants ingested a T_GI pill and donned a GPS enabled watch with heart rate monitoring capabilities prior to the start of the race. Percent off predicted pace (%_OFF) was calculated for seven segments of the race. Separate linear regression analyses were used to assess the relationship between pace, T_​GI, and %BML on relative race performance. One-way ANOVA was used to analyse post race T_GI (≥40°C vs <40°C) on pace and %_OFF.

RESULTS

Larger %BML was associated with faster finish times (R²=0.19, p=0.018), faster average pace (R²=0.29, p=0.012), and a greater %_OFF (R²=0.15, p=0.033). %_OFF during the first mile (1.61km) significantly predicted overall finish time (R²=0.64, p<0.001) while %_OFF during the second mile (3.22km) (R² change=0.18, p<0.001) further added to the model (R²=0.82, p<0.001). Body temperature (pre race T_GI and post race T_GI) was not predictive of overall finish time (p>0.05). There was a trend in a slower pace (p=0.055) and greater %_OFF (p=0.056) in runners finishing the race with a T_GI>40°C.

CONCLUSIONS

Overall, finish time was influenced by greater variations in pace during the first two miles of the race. In addition, runners who minimized fluid losses and had lower T_GI were associated with meeting self-predicted goals.

Sex differences in pacing during 'Ultraman Hawaii'

Background

To date, little is known for pacing in ultra-endurance athletes competing in a non-stop event and in a multi-stage event, and especially, about pacing in a multi-stage event with different disciplines during the stages. Therefore, the aim of the present study was to examine the effect of age, sex and calendar year on triathlon performance and variation of performance by events (i.e., swimming, cycling 1, cycling 2 and running) in ‘Ultraman Hawaii’ held between 1983 and 2015.

Methods

Within each sex, participants were grouped in quartiles (i.e., Q1, Q2, Q3 and Q4) with Q1 being the fastest (i.e., lowest overall time) and Q4 the slowest (i.e., highest overall time). To compare performance among events (i.e., swimming, cycling 1, cycling 2 and running), race time in each event was converted in z score and this value was used for further analysis.

Results

A between-within subjects ANOVA showed a large sex × event (p = 0.015, η² = 0.014) and a medium performance group × event interaction (p = 0.001, η² = 0.012). No main effect of event on performance was observed (p = 0.174, η² = 0.007). With regard to the sex × event interaction, three female performance groups (i.e., Q2, Q3 and Q4) increased race time from swimming to cycling 1, whereas only one male performance group (Q4) revealed a similar trend. From cycling 1 to cycling 2, the two slower female groups (Q3 and Q4) and the slowest male group (Q4) increased raced time. In women, the fastest group decreased (i.e., improved) race time from swimming to cycling 1 and thereafter, maintained performance, whereas in men, the fastest group decreased race time till cycling 2 and increased it in the running.

Conclusion

In summary, women pace differently than men during ‘Ultraman Hawaii’ where the fastest women decreased performance on day 1 and could then maintain on day 2 and 3, whereas the fastest men worsened performance on day 1 and 2 but improved on day 3.

Variables that influence Ironman triathlon performance - what changed in the last 35 years?

OBJECTIVE

This narrative review summarizes findings for Ironman triathlon performance and intends to determine potential predictor variables for Ironman race performance in female and male triathletes.

METHODS

A literature search was performed in PubMed using the terms "Ironman", "triathlon", and "performance". All resulting articles were searched for related citations.

RESULTS

Age, previous experience, sex, training, origin, anthropometric and physiological characteristics, pacing, and performance in split disciplines were predictive. Differences exist between the sexes for anthropometric characteristics. The most important predictive variables for a fast Ironman race time were age of 30-35 years (women and men), a fast personal best time in Olympic distance triathlon (women and men), a fast personal best time in marathon (women and men), high volume and high speed in training where high volume was more important than high speed (women and men), low body fat, low skin-fold thicknesses and low circumference of upper arm (only men), and origin from the United States of America (women and men).

CONCLUSION

These findings may help athletes and coaches to plan an Ironman triathlon career. Age and previous experience are important to find the right point in the life of a triathlete to switch from the shorter triathlon distances to the Ironman distance. Future studies need to correlate physiological characteristics such as maximum oxygen uptake with Ironman race time to investigate their potential predictive value and to investigate socio-economic aspects in Ironman triathlon.

What predicts performance in ultra-triathlon races? - a comparison between Ironman distance triathlon and ultra-triathlon

Objective

This narrative review summarizes recent intentions to find potential predictor variables for ultra-triathlon race performance (ie, triathlon races longer than the Ironman distance covering 3.8 km swimming, 180 km cycling, and 42.195 km running). Results from studies on ultra-triathletes were compared to results on studies on Ironman triathletes.

Methods

A literature search was performed in PubMed using the terms “ultra”, “triathlon”, and “performance” for the aspects of “ultra-triathlon”, and “Ironman”, “triathlon”, and “performance” for the aspects of “Ironman triathlon”. All resulting papers were searched for related citations. Results for ultra-triathlons were compared to results for Ironman-distance triathlons to find potential differences.

Results

Athletes competing in Ironman and ultra-triathlon differed in anthropometric and training characteristics, where both Ironmen and ultra-triathletes profited from low body fat, but ultra-triathletes relied more on training volume, whereas speed during training was related to Ironman race time. The most important predictive variables for a fast race time in an ultra-triathlon from Double Iron (ie, 7.6 km swimming, 360 km cycling, and 84.4 km running) and longer were male sex, low body fat, age of 35–40 years, extensive previous experience, a fast time in cycling and running but not in swimming, and origins in Central Europe.

Conclusion

Any athlete intending to compete in an ultra-triathlon should be aware that low body fat and high training volumes are highly predictive for overall race time. Little is known about the physiological characteristics of these athletes and about female ultra-triathletes. Future studies need to investigate anthropometric and training characteristics of female ultra-triathletes and what motivates women to compete in these races. Future studies need to correlate physiological characteristics such as maximum oxygen uptake (VO_2max) with ultra-triathlon race performance in order to investigate whether these characteristics are also predictive for ultra-triathlon race performance.

Changes in transition times in 'Ironman Hawaii' between 1998 and 2013

BACKGROUND

Recent findings showed that elite Ironman triathletes competing in 'Ironman Hawaii' improved both split and overall race times. The present study investigated whether elite athletes also improved in transition time (i.e. time needed between disciplines for changing clothes and equipment).

METHODS

Changes in split times, overall race times and transition times (i.e. expressed in absolute and relative terms) in the annual fastest competing in 'Ironman Hawaii' were investigated using linear, non-linear and multi-level regression analyses. To detect a potential difference in transition times between different race distances, we compared transition times in 'Ironman Hawaii' to transition times in the World Championships 'Ironman 70.3' covering the half distance of the Ironman distance triathlon.

RESULTS

In 'Ironman Hawaii', transition times remained unchanged for the annual fastest women but increased linearly for the annual fastest men. For the annual ten fastest, transition times increased linearly for women and men in both absolute and relative terms. The sex difference in transition times remained unchanged for the annual fastest, but decreased linearly for the annual ten fastest. In 'Ironman 70.3', transition times remained unchanged for the annual fastest. For the annual ten fastest, transition times decreased linearly for both women and men in absolute and relative terms. The sex difference in transition times remained unchanged for both the annual fastest and the annual ten fastest. Transition times were faster in 'Ironman 70.3' for women in 2011 and for men in 2006, 2007, and 2010-2013. In relative terms, transition times were faster in 'Ironman 70.3'compared to 'Ironman Hawaii' during 2006-2013. The sex difference in transition times remained unchanged.

CONCLUSIONS

In 'Ironman Hawaii', transition times increased for both women and men whereas the sex difference decreased. In 'Ironman 70.3', transition times decreased for both women and men whereas the sex difference remained unchanged. Generally, transition times were slower in 'Ironman Hawaii' compared to 'Ironman 70.3'.